Pharmacokinetics of liposomal encapsulated buprenorphine suspension following subcutaneous administration to cats
Bibliographic record
Abstract
We investigated the effects of liposome encapsulation at prolonging the systemic exposure of buprenorphine following subcutaneous administration in cats. Seven healthy male cats were dosed intravenously with 0.02 mg/kg buprenorphine solution (STD-BUP), followed 14 days later by a subcutaneous injection of 0.2 mg/kg buprenorphine as a liposomal suspension (SUS-BUP) containing drug molecules both in liposomes and the suspending vehicle. Buprenorphine time plasma concentration data for both dosing routes were analyzed simultaneously with four compartmental models. Goodness of fit was assessed both graphically and with the Akaike information criterion. The time-course of intravenous STD-BUP was biphasic, with a 4.39 h average terminal half-life. The subcutaneous SUS-BUP produced plasma buprenorphine concentrations above 0.5 μg/L for more than 96 h, with three distinct peaks in the first 15 h. The model with best fit comprised a central and a peripheral compartment, plus three subcutaneous absorption compartments: one of dissolved drug molecules that were absorbed through a first-order process, and two of liposome-encapsulated drug molecules that were transferred to the solution compartment through separate zero-order processes. Liposomes effectively prolonged the systemic exposure of buprenorphine in cats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".